Showing content from https://github.com/graphdeeplearning/benchmarking-gnns below:
graphdeeplearning/benchmarking-gnns: Repository for benchmarking graph neural networks (JMLR 2023)
Benchmarking Graph Neural Networks
May 10, 2022
- Project based on DGL 0.6.1 and higher. See the relevant dependencies defined in the environment yml files (CPU, GPU).
- Updated technical report of the framework on ArXiv.
- Added AQSOL dataset, which is similar to ZINC for graph regression task, but has a real-world measured chemical target.
- Added mathematical datasets -- GraphTheoryProp and CYCLES which are useful to test GNNs on specific theoretical graph properties.
- Fixed issue #57.
Oct 7, 2020
- Repo updated to DGL 0.5.2 and PyTorch 1.6.0. Please update your environment using yml files (CPU, GPU).
- Added ZINC-full dataset (249K molecular graphs) with scripts.
Jun 11, 2020
- Second release of the project. Major updates :
- Added experimental pipeline for Weisfeiler-Lehman-GNNs operating on dense rank-2 tensors.
- Added a leaderboard for all datasets.
- Updated PATTERN dataset.
- Fixed bug for PATTERN and CLUSTER accuracy.
- Moved first release to this branch.
- New ArXiv's version of the paper.
Mar 3, 2020
- First release of the project.
1. Benchmark installation
Follow these instructions to install the benchmark and setup the environment.
Proceed as follows to download the benchmark datasets.
Use this page to run the codes and reproduce the published results.
Instructions to add a dataset to the benchmark.
5. Adding a Message-passing GCN
Step-by-step directions to add a MP-GCN to the benchmark.
6. Adding a Weisfeiler-Lehman GNN
Step-by-step directions to add a WL-GNN to the benchmark.
Full leaderboards coming soon on paperswithcode.com.
ArXiv's paper
@article{dwivedi2020benchmarkgnns,
title={Benchmarking Graph Neural Networks},
author={Dwivedi, Vijay Prakash and Joshi, Chaitanya K and Luu, Anh Tuan and Laurent, Thomas and Bengio, Yoshua and Bresson, Xavier},
journal={arXiv preprint arXiv:2003.00982},
year={2020}
}
RetroSearch is an open source project built by @garambo
| Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4
